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Record W3088051466 · doi:10.21037/apm-20-553

Dignity therapy for patients with brain tumours: qualitative reports from patients, caregivers and practitioners

2020· article· en· W3088051466 on OpenAlexaffabout
Melissa B. Korman, Janet Ellis, Jennifer Moore, Denise Bilodeau, Sarah Dulmage, Margaret I. Fitch, Christina Mueller, Arjun Sahgal, Claire Moroney

Bibliographic record

VenueAnnals of Palliative Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsSunnybrook Health Science CentreHealth Sciences Centre
Fundersnot available
KeywordsMedicineDignityQualitative researchFamily medicineIntensive care medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Most individuals with brain tumours experience distress or cognitive impairment during the illness trajectory, potentially causing decreased quality of life, strain on interpersonal relationships and altered sense of self or of the world. Symptoms of brain tumour and treatment can cause increased reliance on others and decreased in sense of dignity. Dignity is an important consideration when caring for patients, as it can influence decisions at end-of-life. Dignity therapy (DT) is a therapeutic intervention that was developed for patients near the end of life. DT encourages the patient to reflect on the life lived, including important roles and sources of pride, resulting in the development of a 'Legacy Document'. DT has been shown to enhance quality of life and dignity, and reduce psychological and existential distress for patients at the end-of-life. There is little literature on the effectiveness of DT, or other quality of life interventions, in brain tumour populations; This paper reports on the feasibility of conducting DT with this population, and presents qualitative data gathered from patients with brain tumours who participated in DT, their caregivers, and their Dignity Therapists. METHODS: Participants were recruited from the Odette Cancer Centre in Toronto. One of five Dignity Therapists conducted the intervention; time data was logged. Immediately after the intervention, patient participants, their caregivers, and Dignity Therapists were sent an open-ended, self-report survey about their experience with DT. Qualitative content analysis was conducted by an impartial reviewer. Average time taken to conduct the intervention was determined. RESULTS: Fifteen out of the 17 recruited participants (88%) completed the intervention; 2 were unable to complete the intervention due to progressing disease. Qualitative data was categorized according to two main areas of interest: Acceptability and Impact. Four participants, 5 caregivers and 4 care providers completed the qualitative surveys. All 4 patient participants reported benefits of DT that related to communication and/or advanced care planning (ACP). Dignity therapists felt that the impact on their patients was positive, and reported satisfaction as a clinician. CONCLUSIONS: The low attrition rate for the intervention suggests that DT is feasible in this population, though the required time to complete DT might be difficult for healthcare practitioners to provide within the recommended timeframe for this therapy. Positive qualitative reports on the effect of DT from patients, caregivers and dignity therapists alike indicate that DT is a promising intervention for this demographic.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.037
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.037
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0090.008
Scholarly communication0.0040.004
Open science0.0020.007
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.160
GPT teacher head0.407
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2020
Admission routes2
Has abstractyes

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